In this article, we demonstrate how you can easily summarize a text using Pytorch within a few simple steps. The model that we are going to be using is already pretrained, so no additional training is required :)

Abstractive Summarization is a task in Natural Language Processing (NLP) that aims to generate a concise summary of a source text. Unlike extractive summarization, abstractive summarization does not simply copy important phrases from the source text but also potentially come up with new phrases that are relevant, which can be seen as paraphrasing. Abstractive summarization yields a number of applications in different domains, from books and literature, to science and R&D, to financial research and legal documents analysis.

To date, the most recent and effective approach toward abstractive summarization is using transformer models fine-tuned specifically on a summarization dataset.

So without further ado, let’s get started!

#data-science #deep-learning #machine-learning #pytorch #python